Environmental concerns, as well as consumers' awareness of buying green or environmentally-friendly products, has a positive impact on the emergence of the green market. The emerging green market brings many opportunities in different fields. Today, the issue of green entrepreneurship and sustainable development aim at producing environmentally-friendly products. This is indeed welcomed in the emerging green market. The publicly available research studies that investigate how green entrepreneurship, sustainable development, and emerging green markets are interconnected with each other are limited. More specifically, the impact of the green market on green entrepreneurship and sustainable development has not yet been studied completely. Therefore, a comprehensive research model has been developed in this paper based on the literature. The developed model is then tested using IBM SPSS Statistics for Windows, Version 19. IBM Corp.: Armonk, NY, USA and Smart-PLS Version 2 based on the data collected via a survey from a sample of knowledge-based companies in the Science & Technology Park of Tehran University. The results of the research indicate a positive and significant effect of the emergence of the green market on green entrepreneurship and sustainable development in knowledge-based companies. Moreover, the impact of the green entrepreneurship structure on sustainable development has been studied and the result presents that green entrepreneurship has a positive and significant effect on sustainable development.

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This paper examines and analytically reviews the thermal management systems proposed over the past six decades for gas turbine civil aero engines. The objective is to establish the evident system shortcomings and to identify the remaining research questions that need to be addressed to enable this important technology to be adopted by next generation of aero engines with complicated designs. Future gas turbine aero engines will be more efficient, compact and will have more electric parts. As a result, more heat will be generated by the different electrical components and avionics. Consequently, alternative methods should be used to dissipate this extra heat as the current thermal management systems are already working on their limits. For this purpose, different structures and ideas in this field are stated in terms of considering engines architecture, the improved engine efficiency, the reduced emission level and the improved fuel economy. This is followed by a historical coverage of the proposed concepts dating back to 1958. Possible thermal management systems development concepts are then classified into four distinct classes: classic, centralized, revolutionary and cost-effective; and critically reviewed from challenges and implementation considerations points of view. Based on this analysis, the potential solutions for dealing with future challenges are proposed including combination of centralized and revolutionary developments and combination of classic and cost-effective developments. The effectiveness of the proposed solutions is also discussed with a complexity-impact correlation analysis.

Utilizing meta-heuristic global optimization algorithms in gas turbine aero-engines modelling and control problems is proposed over the past two decades as a methodological approach. The purpose of the review is to establish evident shortcomings of these approaches and to identify the remaining research challenges. These challenges need to be addressed to enable the novel, cost-effective techniques to be adopted by aero-engine designers. First, the benefits of global optimization algorithms are stated in terms of philosophy and the nature of different types of these methods. Then, a historical coverage is given for the applications of different optimization techniques applied in different aspects of gas turbine modelling, controller design, and tuning fields. The main challenges for the application of meta-heuristic global optimization algorithms in new advanced engine designs are presented. To deal with these challenges, two efficient optimization algorithms, Competent Genetic Algorithm in single objective feature and aggregative gradient-based algorithm in multi-objective feature are proposed and applied in a turbojet engine controller gaintuning problem as a case study. A comparison with the publicly available results show that optimization time and convergence indices will be enhanced noticeably. Based on this comparison and analysis, the potential solutions for the remaining research challenges for application to aerospace engineering problems in the future include the implementation of enhanced and modified optimization algorithms and hybrid optimization algorithms in order to achieve optimal results for the advanced engine modelling and controller design procedure with affordable computational effort.

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